Twitter Trend Analysis Using Latent Dirichlet Allocation

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The community of users participating in social media tends to share about common interests at the same time, giving rise to what are known as social trends. A social trend reflects the voice of a large number of users which, for some reason, becomes popular in a specific moment. Through social trends, users therefore suggest that some occurrence of wide interest is taking place and subsequently triggering the trend. In this work, we explore the types of triggers that spark trends on the microblogging site Twitter, and introduce a typology that includes the following four types: news, ongoing events, memes, and commemoratives. The user will be allowed to search for the latest trends by inputting a keyword into search field. Based on user provided keyword, the system will search for similar keywords in database and summarize the total count to provide the trending tweets on twitter. The trending tweets with hashtag (#) will be displayed first and then the rest words will be displayed. By clicking on every trending tweet, the user commented tweets will be displayed. User can view all the tweets from the searched keyword.

  • People will get to know about the trending tweets on tweeter.
  • System will allow user to input a keyword and search for trending tweet.
  • System will provide accurate results based on user inputted keyword.
  • Will provide inaccurate results if keyword not entered correctly

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